In 2024, over 74 million women in Brazil were aged between 15 and 64 years old. The youngest age range - from 0 to 14 years - is the only one where the male population exceeds that of women. That year, the population of Brazil was estimated at over 212 million inhabitants.

About this dataset

Context

The dataset tabulates the population of Brazil by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Brazil. The dataset can be utilized to understand the population distribution of Brazil by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Brazil. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Brazil.

Key observations

Largest age group (population): Male # 25-29 years (373) | Female # 0-4 years (346). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Brazil population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Brazil is shown in the following column.
• Population (Female): The female population in the Brazil is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Brazil for each age group.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Brazil Population by Gender. You can refer the same here

Brazil BR: Sex Ratio at Birth: Male Births per Female Births data was reported at 1.045 Ratio in 2023. This stayed constant from the previous number of 1.045 Ratio for 2022. Brazil BR: Sex Ratio at Birth: Male Births per Female Births data is updated yearly, averaging 1.045 Ratio from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 1.047 Ratio in 1993 and a record low of 1.043 Ratio in 1979. Brazil BR: Sex Ratio at Birth: Male Births per Female Births data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Brazil – Table BR.World Bank.WDI: Population and Urbanization Statistics. Sex ratio at birth refers to male births per female births.;United Nations Population Division. World Population Prospects: 2024 Revision.;Weighted average;

About this dataset

Context

The dataset tabulates the data for the Brazil, IN population pyramid, which represents the Brazil population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Brazil, IN, is 29.7.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Brazil, IN, is 29.1.
• Total dependency ratio for Brazil, IN is 58.7.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Brazil, IN is 3.4.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Brazil population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Brazil for the selected age group is shown in the following column.
• Population (Female): The female population in the Brazil for the selected age group is shown in the following column.
• Total Population: The total population of the Brazil for the selected age group is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Brazil Population by Age. You can refer the same here

In 2023, more than three million people resided in the Federal District of Brazil. Of these, 52 percent accounted for the female population, while the male population made up nearly 48 percent. The data reported for the region is similar to national data for the same year, where approximately 51 percent of the Brazilian population were female.

In 2023, women constituted the majority of the population in the Federal District of Brazil. The largest age group was women aged between 40 and 49 years old.

This scatter chart displays female population (people) against male population (people) in Brazil. The data is about countries per year.

The total population in Brazil was estimated at 212.6 million people in 2024, according to the latest census figures and projections from Trading Economics. This dataset provides - Brazil Population - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Between 1980 and 2049, the mean annual increase of the economically active population in Brazil was higher among women than men. The growth rate of economically active women reached 3.98 percent in 1993 and 1994. However, the growth rate started contracting in the late 1990s and, by 2034, it is expected to reach negative values. In the case of men, the annual increase of the economically active population is not forecast to register negative values until 2039, with projections showing a decline to -0.23 percent by 2049.

In 2023, there were nearly 40 million homes led by women in Brazil, approximately 2.5 million more than a year earlier. The number of households led by men increased from 36.3 million in 2021 to 37.5 million in 2023. This opposite trend in the development of households whose head were women and men has been witnessed since 2015.

Background In Brazil coronary heart disease (CHD) constitutes the most important cause of death in both sexes in all the regions of the country and interestingly, the difference between the sexes in the CHD mortality rates is one of the smallest in the world because of high rates among women. Since a question has been raised about whether or how the incidence of several CHD risk factors differs between the sexes in Brazil the prevalence of various risk factors for CHD such as high blood cholesterol, diabetes mellitus, hypertension, obesity, sedentary lifestyle and cigarette smoking was compared between the sexes in a Brazilian population; also the relationships between blood cholesterol and the other risk factors were evaluated. Results The population presented high frequencies of all the risk factors evaluated. High blood cholesterol (CHOL) and hypertension were more prevalent among women as compared to men. Hypertension, diabetes and smoking showed equal or higher prevalence in women in pre-menopausal ages as compared to men. Obesity and physical inactivity were equally prevalent in both sexes respectively in the postmenopausal age group and at all ages. CHOL was associated with BMI, sex, age, hypertension and physical inactivity. Conclusions In this population the high prevalence of the CHD risk factors indicated that there is an urgent need for its control; the higher or equal prevalences of several risk factors in women could in part explain the high rates of mortality from CHD in females as compared to males.

In 2025, 28 percent of male respondents in Brazil strongly or somewhat defined themselves as feminists. Among the female respondents, this figure rose to 46 percent.

About this dataset

Context

The dataset tabulates the population of Brazil by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Brazil across both sexes and to determine which sex constitutes the majority.

Key observations

There is a majority of female population, with 53.6% of total population being female. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Brazil is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Brazil total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Brazil Population by Race & Ethnicity. You can refer the same here

ABSTRACT - BACKGROUND: Gallbladder diseases (GBD) are one of the most common medical conditions requiring surgical intervention, both electively and urgently. It is widely accepted that sex and ethnic characteristics mighty influence both prevalence and outcomes. AIM: This study aimed to evaluate the differences on distributions of gender and ethnicity related to the epidemiology of GBD in the Brazilian public health system. METHODS: DATASUS was used to retrieve patients’ data recorded under the International Code of Diseases (ICD-10) - code K80 from January 2008 to December 2019. The number of admissions, modality of care, number of deaths, and in-hospital mortality rate were analyzed by gender and ethnic groups. RESULTS: Between 2008 and 2019, a total of 2,899,712 patients with cholelithiasis/cholecystitis (K80) were admitted to the hospitals of the Brazilian Unified Health System, of whom only 22.7% were males. Yet, the in-hospital mortality rate was significantly higher in males (15.9 per 1,000 male patients) than females (6.3 per 1,000 female patients) (p

Abstract

Different countries have different health outcomes that are in part due to the way respective health systems perform. Regardless of the type of health system, individuals will have health and non-health expectations in terms of how the institution responds to their needs. In many countries, however, health systems do not perform effectively and this is in part due to lack of information on health system performance, and on the different service providers.

The aim of the WHO World Health Survey is to provide empirical data to the national health information systems so that there is a better monitoring of health of the people, responsiveness of health systems and measurement of health-related parameters.

The overall aims of the survey is to examine the way populations report their health, understand how people value health states, measure the performance of health systems in relation to responsiveness and gather information on modes and extents of payment for health encounters through a nationally representative population based community survey. In addition, it addresses various areas such as health care expenditures, adult mortality, birth history, various risk factors, assessment of main chronic health conditions and the coverage of health interventions, in specific additional modules.

The objectives of the survey programme are to: 1. develop a means of providing valid, reliable and comparable information, at low cost, to supplement the information provided by routine health information systems. 2. build the evidence base necessary for policy-makers to monitor if health systems are achieving the desired goals, and to assess if additional investment in health is achieving the desired outcomes. 3. provide policy-makers with the evidence they need to adjust their policies, strategies and programmes as necessary.

Geographic coverage

The survey sampling frame must cover 100% of the country's eligible population, meaning that the entire national territory must be included. This does not mean that every province or territory need be represented in the survey sample but, rather, that all must have a chance (known probability) of being included in the survey sample.

There may be exceptional circumstances that preclude 100% national coverage. Certain areas in certain countries may be impossible to include due to reasons such as accessibility or conflict. All such exceptions must be discussed with WHO sampling experts. If any region must be excluded, it must constitute a coherent area, such as a particular province or region. For example if ¾ of region D in country X is not accessible due to war, the entire region D will be excluded from analysis.

Analysis unit

Households and individuals

Universe

The WHS will include all male and female adults (18 years of age and older) who are not out of the country during the survey period. It should be noted that this includes the population who may be institutionalized for health reasons at the time of the survey: all persons who would have fit the definition of household member at the time of their institutionalisation are included in the eligible population.

If the randomly selected individual is institutionalized short-term (e.g. a 3-day stay at a hospital) the interviewer must return to the household when the individual will have come back to interview him/her. If the randomly selected individual is institutionalized long term (e.g. has been in a nursing home the last 8 years), the interviewer must travel to that institution to interview him/her.

The target population includes any adult, male or female age 18 or over living in private households. Populations in group quarters, on military reservations, or in other non-household living arrangements will not be eligible for the study. People who are in an institution due to a health condition (such as a hospital, hospice, nursing home, home for the aged, etc.) at the time of the visit to the household are interviewed either in the institution or upon their return to their household if this is within a period of two weeks from the first visit to the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLING GUIDELINES FOR WHS

Surveys in the WHS program must employ a probability sampling design. This means that every single individual in the sampling frame has a known and non-zero chance of being selected into the survey sample. While a Single Stage Random Sample is ideal if feasible, it is recognized that most sites will carry out Multi-stage Cluster Sampling.

The WHS sampling frame should cover 100% of the eligible population in the surveyed country. This means that every eligible person in the country has a chance of being included in the survey sample. It also means that particular ethnic groups or geographical areas may not be excluded from the sampling frame.

The sample size of the WHS in each country is 5000 persons (exceptions considered on a by-country basis). An adequate number of persons must be drawn from the sampling frame to account for an estimated amount of non-response (refusal to participate, empty houses etc.). The highest estimate of potential non-response and empty households should be used to ensure that the desired sample size is reached at the end of the survey period. This is very important because if, at the end of data collection, the required sample size of 5000 has not been reached additional persons must be selected randomly into the survey sample from the sampling frame. This is both costly and technically complicated (if this situation is to occur, consult WHO sampling experts for assistance), and best avoided by proper planning before data collection begins.

All steps of sampling, including justification for stratification, cluster sizes, probabilities of selection, weights at each stage of selection, and the computer program used for randomization must be communicated to WHO

STRATIFICATION

Stratification is the process by which the population is divided into subgroups. Sampling will then be conducted separately in each subgroup. Strata or subgroups are chosen because evidence is available that they are related to the outcome (e.g. health, responsiveness, mortality, coverage etc.). The strata chosen will vary by country and reflect local conditions. Some examples of factors that can be stratified on are geography (e.g. North, Central, South), level of urbanization (e.g. urban, rural), socio-economic zones, provinces (especially if health administration is primarily under the jurisdiction of provincial authorities), or presence of health facility in area. Strata to be used must be identified by each country and the reasons for selection explicitly justified.

Stratification is strongly recommended at the first stage of sampling. Once the strata have been chosen and justified, all stages of selection will be conducted separately in each stratum. We recommend stratifying on 3-5 factors. It is optimum to have half as many strata (note the difference between stratifying variables, which may be such variables as gender, socio-economic status, province/region etc. and strata, which are the combination of variable categories, for example Male, High socio-economic status, Xingtao Province would be a stratum).

Strata should be as homogenous as possible within and as heterogeneous as possible between. This means that strata should be formulated in such a way that individuals belonging to a stratum should be as similar to each other with respect to key variables as possible and as different as possible from individuals belonging to a different stratum. This maximises the efficiency of stratification in reducing sampling variance.

MULTI-STAGE CLUSTER SELECTION

A cluster is a naturally occurring unit or grouping within the population (e.g. enumeration areas, cities, universities, provinces, hospitals etc.); it is a unit for which the administrative level has clear, nonoverlapping boundaries. Cluster sampling is useful because it avoids having to compile exhaustive lists of every single person in the population. Clusters should be as heterogeneous as possible within and as homogenous as possible between (note that this is the opposite criterion as that for strata). Clusters should be as small as possible (i.e. large administrative units such as Provinces or States are not good clusters) but not so small as to be homogenous.

In cluster sampling, a number of clusters are randomly selected from a list of clusters. Then, either all members of the chosen cluster or a random selection from among them are included in the sample. Multistage sampling is an extension of cluster sampling where a hierarchy of clusters are chosen going from larger to smaller.

In order to carry out multi-stage sampling, one needs to know only the population sizes of the sampling units. For the smallest sampling unit above the elementary unit however, a complete list of all elementary units (households) is needed; in order to be able to randomly select among all households in the TSU, a list of all those households is required. This information may be available from the most recent population census. If the last census was >3 years ago or the information furnished by it was of poor quality or unreliable, the survey staff will have the task of enumerating all households in the smallest randomly selected sampling unit. It is very important to budget for this step if it is necessary and ensure that all households are properly enumerated in order that a representative sample is obtained.

It is always best to have as many clusters in the PSU as possible. The reason for this is that the fewer the number of respondents in each PSU, the lower will be the clustering effect which

In 2018, approximately ** percent of women surveyed in Brazil were deemed functionally literate – that is, minimally able to read and interpret memos, pieces of news, instructions, narratives, graphs, tables, ads, and other types of text. Among men, the functional literacy rate stood at ** percent. Overall, the share of population deemed functionally literate in Brazil has decreased.

According to a survey conducted in Brazil from March to August 2024, around 84 percent of female respondents had accessed the internet. Around 85 percent of their male counterparts used the web. Overall, it has been estimated that over 84 percent of the population of Brazil was online in 2024.

About this dataset

Context

The dataset tabulates the Brazil population by age. The dataset can be utilized to understand the age distribution and demographics of Brazil.

Content

The dataset constitues the following three datasets

• Brazil, IN Age Group Population Dataset: A complete breakdown of Brazil age demographics from 0 to 85 years, distributed across 18 age groups
• Brazil, IN Age Cohorts Dataset: Children, Working Adults, and Seniors in Brazil - Population and Percentage Analysis
• Brazil, IN Population Pyramid Dataset: Age Groups, Male and Female Population, and Total Population for Demographics Analysis

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

The average monthly income per person in Brazil is higher for male workers than for their female counterparts. In 2024, the gap was of *** Brazilian reals per month. Overall, that year the monthly income per capita for the working population in Brazil was ***** reals, the highest income since, at least, 2018.

As of January 2025, about 59 million people lived in Italy. Around 29 million individuals were males and 30 million people were females. The most populated area of the country was the north-west, where 15.9 million people lived. Furthermore, the southern regions counted 13.4 million inhabitants, representing the second most populous area of the country. Regional census The northern region of Lombardy is the most populous region of Italy. One-sixth of all the Italian population is concentrated in this area. Lazio and Campania follow with approximately 5.7 million and 5.6 million individuals, respectively. On the other hand, Aosta Valley, a northern region bordering to France and Switzerland, counted 123,000 inhabitants, representing the smallest region of Italy in terms of residents as well as area. More and more Italians are moving abroad In recent years, the number of Italians reported living abroad increased. In 2022, 5.8 million people lived outside Italy, almost three million more than in 2006. The country hosting the largest Italian population is Argentina, while other large Italian communities reside in Germany, Switzerland, and Brazil.